[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DKAQ05080CYY9DM10CPHJG":3,"skill-same:01M6DKAQ05080CYY9DM10CPHJG":137},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":37,"publishedAt":58,"linkOnly":59,"markdownContent":60,"markdownBody":61,"frontMatter":62,"refName":80,"commitSha":81,"skillDirectory":82,"forksCount":83,"repositoryHtmlUrl":84,"repositoryHomepageUrl":85,"ownerHtmlUrl":86,"ownerBlogUrl":87,"ownerDescription":88,"updatedAt":89,"install":90,"resources":102},"01M6DKAQ05080CYY9DM10CPHJG","higgsfield-generate",null,"Use when the user wants to generate an image or video via Higgsfield AI. Covers\n30+ models: Soul V2, Seedance 2.0, Kling 3.0, Veo 3.1, GPT Image 2, Nano Banana 2.\nAlso covers Marketing Studio — branded ad video\u002Fimage with avatars and products.\nUse whenever: \"generate an image\", \"make a video\", \"animate this photo\",\n\"image-to-video\", \"img2vid\", \"edit this image with AI\", \"produce a clip\",\n\"create an ad\", \"make a UGC video\", \"marketing video\", \"brand video\",\n\"TV spot\", \"import product from URL\", \"create avatar for ad\",\n\"Seedance\", \"Kling\", \"Veo\", \"Soul gen\", \"Nano Banana\", \"Marketing Studio\".\nChain with higgsfield-soul-id when user wants a reusable face identity.\nOwns AI-generated \"marketing video\" \u002F \"brand video\" \u002F ad creative.\nNOT for: training a Soul Character (use higgsfield-soul-id), product photoshoots\nwith mode-specific enhancer (use higgsfield-product-photoshoot), text\u002FTTS,\nscreen-recorded product demos (use marketing-demo), slides-to-MP4 assembly\n(use video-content), Remotion code (use remotion-best-practices).\nRequires Higgsfield CLI installed and authed.","MoizIbnYousaf\u002Fmarketing-cli","MoizIbnYousaf","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F148609638?v=4","01M6DK31T63X0A4VD3HV88V5E4","Abdul Moiz Shahzad","01M6DK31ZWA28MZK3202BZRXAB",35,"MIT","https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fhiggsfield-generate\u002FSKILL.md",[18,23,26,29,34],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000019","营销推广",{"categoryNo":27,"categoryName":28,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":30,"categoryName":31,"taxonomyType":32,"taxonomyTypeDesc":33},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",{"categoryNo":35,"categoryName":36,"taxonomyType":32,"taxonomyTypeDesc":33},"01JBSEEDCAT000000000000035","市场营销",[38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57],"higgsfield generate","higgsfield","generate","ad creative","chain","banana","soul","generated","ugc video","model","text","image","Bash","Remotion","Video","product","code","create","training","cli","2026-11-10 10:12:30",false,"---\nname: higgsfield-generate\nversion: 0.3.0\ndescription: |\n  Use when the user wants to generate an image or video via Higgsfield AI. Covers\n  30+ models: Soul V2, Seedance 2.0, Kling 3.0, Veo 3.1, GPT Image 2, Nano Banana 2.\n  Also covers Marketing Studio — branded ad video\u002Fimage with avatars and products.\n  Use whenever: \"generate an image\", \"make a video\", \"animate this photo\",\n  \"image-to-video\", \"img2vid\", \"edit this image with AI\", \"produce a clip\",\n  \"create an ad\", \"make a UGC video\", \"marketing video\", \"brand video\",\n  \"TV spot\", \"import product from URL\", \"create avatar for ad\",\n  \"Seedance\", \"Kling\", \"Veo\", \"Soul gen\", \"Nano Banana\", \"Marketing Studio\".\n  Chain with higgsfield-soul-id when user wants a reusable face identity.\n  Owns AI-generated \"marketing video\" \u002F \"brand video\" \u002F ad creative.\n  NOT for: training a Soul Character (use higgsfield-soul-id), product photoshoots\n  with mode-specific enhancer (use higgsfield-product-photoshoot), text\u002FTTS,\n  screen-recorded product demos (use marketing-demo), slides-to-MP4 assembly\n  (use video-content), Remotion code (use remotion-best-practices).\n  Requires Higgsfield CLI installed and authed.\nargument-hint: \"[prompt] [--model \u003Cname>] [--image \u003Cpath-or-id>]\"\nallowed-tools:\n  - Bash\n  - Read\n  - Write\n  - Edit\n  - Skill\nreads:\n  - brand\u002Fvoice-profile.md\n  - brand\u002Fcreative-kit.md\nwrites: []\nauthor: Higgsfield AI (ported by moiz)\nlicense: MIT\nuser-invocable: true\nmetadata:\n  openclaw:\n    emoji: ?\n---\n\n# \u002Fhiggsfield-generate — AI Image & Video Generation via Higgsfield\n\nSubmit jobs to any Higgsfield model. Wraps the `higgsfield` CLI. Covers generic image\u002Fvideo gen and Marketing Studio (branded ads, avatars, products).\n\n## When to use\n\n- User wants an image or video generated by AI — any model, any style\n- \"animate this photo\", \"make a video from an image\", \"img2vid\"\n- \"create a UGC ad\", \"Marketing Studio video\", \"brand video with avatar\"\n- \"import this product URL and make an ad\"\n- \"generate a cinematic still\", \"make a character illustration\"\n- Anything involving Seedance, Kling, Veo, Soul, Nano Banana, Flux, GPT Image\n\n**Route elsewhere if:**\n- User wants to train a reusable face identity → `higgsfield-soul-id`\n- User wants a mode-enhanced product photoshoot → `higgsfield-product-photoshoot`\n- User just needs a one-off image without Higgsfield → `image-gen` (Gemini, free tier)\n\n## On Activation\n\n1. Read `brand\u002Fvoice-profile.md` and `brand\u002Fcreative-kit.md` if present (`creative-kit.md` is written by `\u002Fvisual-style`). Use brand context to inform model choice and prompt style where relevant. All files are optional — zero-context operation is fine.\n2. Check CLI: `higgsfield account status`. If not on `$PATH`, surface install command (see Optional dependency section). If session expired, prompt auth.\n3. Pick a model from the workflow below. Ask one question at a time if context is missing.\n\n## Optional dependency — Higgsfield account\n\nThis skill requires the `@higgsfield\u002Fcli` binary and a Higgsfield account.\n\n**Without the CLI installed**, return a clear actionable error:\n```\nhiggsfield CLI not found. Install with:\n  curl -fsSL https:\u002F\u002Fraw.githubusercontent.com\u002Fhiggsfield-ai\u002Fcli\u002Fmain\u002Finstall.sh | sh\nThen authenticate:\n  higgsfield auth login\n```\n\n**Without an authed Higgsfield account**, the CLI itself surfaces the auth prompt — no special handling needed in the skill.\n\n**Fallback for image generation only:** if the user just needs a one-off image and doesn't have a Higgsfield account, route them to `image-gen` (Gemini, model `gemini-3.1-flash-image-preview`, free tier). Video generation, Marketing Studio, Soul Characters, and product modes have no fallback — they require Higgsfield.\n\n## Step 0 — Bootstrap\n\nBefore any other command, make sure the CLI is installed and authenticated:\n\n1. If `higgsfield` is not on `$PATH`, install it:\n   ```bash\n   curl -fsSL https:\u002F\u002Fraw.githubusercontent.com\u002Fhiggsfield-ai\u002Fcli\u002Fmain\u002Finstall.sh | sh\n   ```\n2. If `higgsfield account status` fails with `Session expired` \u002F `Not authenticated`, ask the user to run `higgsfield auth login` (interactive, opens a browser) and wait for them to confirm before continuing.\n\nSkip both checks if `higgsfield account status` already prints account info.\n\n## UX Rules\n\n1. Be concise. No raw IDs, no JSON dumps in chat. Print result URL when ready.\n2. No internal jargon. Don't narrate \"calling higgsfield cost\", \"polling job\".\n3. Detect the user's language from the first message and reply in it. Technical args (`--aspect_ratio 16:9`) stay English.\n4. Don't batch-ask. Pick a sane default model and ask one thing at a time only if genuinely missing.\n5. Don't pre-estimate cost. Just submit unless the user asks.\n6. Pass `--wait` to `generate create` so the command blocks until done and prints the result URL itself. Avoid the two-step `create` → `wait` pattern.\n\n## Workflow — generic generation\n\n1. **Pick a model.** Practical defaults from production use:\n\n   **Image:**\n   - Brand product visual (Pinterest pin, lifestyle, hero banner, ad pack, virtual try-on) → use `higgsfield-product-photoshoot` instead. NOT this skill.\n   - Branded ad image with avatar + product (Marketing Studio shape) → Marketing Studio Image (see Marketing Studio below)\n   - Aesthetic UGC \u002F fashion editorial \u002F lifestyle character → Soul 2.0\n   - Cinematic still frame → Soul Cinema\n   - Highly characterful creative persona (text-only, distinctive) → Soul Cast\n   - Locations \u002F environments \u002F no-people scenes → Soul Location (best in class)\n   - Vector illustrations OR face edit + complex scene swap → Seedream 4.5\n   - Soul Character (reference id from `higgsfield-soul-id`) → Soul 2.0 for stills, Soul Cinema for cinematic\n   - Fast and cheap iteration → Z Image\n   - Character or cartoon-style work → Nano Banana 2; step up to Nano Banana Pro on hard cases\n   - **Default for everything else → GPT Image 2.** Graphic design, UI, banners, typography, and high-fidelity general generation.\n\n   **Video:**\n   - All advertising \u002F commercial \u002F branded ad video → Marketing Studio (see Marketing Studio below)\n   - **Default all-purpose serious video (multi-shot, consistent identity, motion-heavy) → Seedance 2.0.** SOTA.\n   - Single-plane scene without strong dynamics, cheaper than Seedance 2.0 → Kling 3.0\n   - Cheap clean shot without cuts → Seedance 1.5 Pro\n   - Cinema-grade highest fidelity → Cinema Studio Video 3.0\n   - Cheap with strong physics, no audio needed → Minimax Hailuo\n   - Fast batch \u002F volume → Veo 3.1 Lite\n\n   For the actual `--model` ID to pass to `higgsfield generate create`, run `higgsfield model list --json | jq` to map display names to IDs. See `references\u002Fmodel-catalog.md` for the full table.\n\n2. **Pass media inputs straight to flags.** Media flags accept a local file path **or** a UUID. CLI auto-uploads paths and auto-detects job vs upload for UUIDs. No need to pre-upload. Each model declares accepted roles (`image`, `start_image`, `end_image`, `video`, `audio`) — see `references\u002Fmedia-inputs.md`.\n3. **Validate quickly.** If unsure of params, run `higgsfield model get \u003Cjst> --json` once and pass only what's needed. Use schema defaults otherwise. The server returns `adjustments` for non-fatal coercions and a structured error for invalid declared-param values.\n4. **Submit and wait in one shot.** `higgsfield generate create \u003Cjst> --prompt \"...\" [media flags] [param flags] --wait`. Blocks until terminal status and prints the result URL on stdout. Tunables: `--wait-timeout 20m` (default 10m), `--wait-interval 5s` (default 3s).\n5. **Deliver.** Send the URL plus a one-line summary (model, duration if video).\n\nTo inspect or rerun later, `higgsfield generate list --json` and `higgsfield generate get \u003Cid> --json` work for retrospection. `higgsfield generate wait \u003Cid>` is still available if you ever need to rejoin a job started without `--wait`.\n\n## Media flags\n\n| Flag | Use for | Models that accept it |\n|---|---|---|\n| `--image \u003Cpath-or-id>` | reference image | most image models, `seedance_2_0`, `veo3`, `marketing_studio_video` |\n| `--start-image \u003Cpath-or-id>` | first frame for image-to-video transitions | `kling3_0`, `kling2_6`, `veo3_1`, `seedance_2_0`, `marketing_studio_video` |\n| `--end-image \u003Cpath-or-id>` | last frame for transitions | `kling3_0`, `seedance_2_0`, `marketing_studio_video` |\n| `--video \u003Cpath-or-id>` | reference video | `seedance_2_0` |\n| `--audio \u003Cpath-or-id>` | reference audio (lipsync, soundtrack match) | `seedance_2_0` (use this, NOT `--generate-audio`) |\n\nEach flag accepts either a local file path (auto-uploaded) or a UUID. See `references\u002Fmedia-inputs.md` for the full table.\n\n## Common params\n\nFlags pass through to model schema. Use `higgsfield model get \u003Cjst>` to discover.\n\n```bash\nhiggsfield generate create gpt_image_2 --prompt \"neon city at dusk\" --aspect_ratio 16:9 --resolution 2k --wait\nhiggsfield generate create nano_banana_2 --prompt \"anime character concept, expressive pose\" --image .\u002Fref.png --wait\nhiggsfield generate create seedance_2_0 --prompt \"camera dollies in\" --start-image .\u002Ffirst.png --duration 8 --wait\nhiggsfield generate create text2image_soul_v2 --prompt \"...\" --soul-id \u003Csoul_ref_id> --wait\n```\n\nFor machine-readable output, add `--json`. With `--wait --json` you get the final job object array.\n\nStdin prompt: `echo \"...\" | higgsfield generate create z_image --wait`.\n\n## Marketing Studio\n\nBranded image\u002Fvideo gen: avatars + products + ad-style modes. Use models `marketing_studio_video` and `marketing_studio_image`.\n\n### Concepts\n\n- **Avatar** — presenter face. Curated `preset` (browse `higgsfield marketing-studio avatars list`) or `custom` (uploaded photos via `higgsfield marketing-studio avatars create`).\n- **Product** — brand item with title + reference images. Imported from URL (`higgsfield marketing-studio products fetch --url ...`) or created from uploaded images (`higgsfield marketing-studio products create`).\n- **Webproduct** — App Store \u002F web page version. Auto-routes when fetching App Store URLs.\n\n### UX rules (additional)\n\n- One question per phase. Don't ask product+avatar+mode upfront.\n\n### Workflow — quick ad video\n\n1. **Get product.**\n   - URL → `higgsfield marketing-studio products fetch --url \u003Curl> --wait` (polls until import done)\n   - Local images → `higgsfield upload create \u003Cphoto>...` then `higgsfield marketing-studio products create --title \"...\" --image \u003Cid>...`\n   Capture product id.\n2. **Pick avatar.**\n   - Default: `higgsfield marketing-studio avatars list` and pick a preset matching the brand voice.\n   - Custom: `higgsfield marketing-studio avatars create --name \"...\" --image \u003Cupload_id>`.\n3. **Pick mode.** Default `ugc`. Other slugs: `tutorial`, `ugc_unboxing`, `hyper_motion`, `product_review`, `tv_spot`, `wild_card`, `ugc_virtual_try_on`, `virtual_try_on`. See `references\u002Fmarketing-modes.md`.\n4. **Generate (one-shot).**\n   ```bash\n   higgsfield generate create marketing_studio_video \\\n     --prompt \"...\" \\\n     --avatars '[{\"id\":\"\u003Cavatar_id>\",\"type\":\"preset\"}]' \\\n     --product_ids '[\u003Cproduct_id>]' \\\n     --mode ugc \\\n     --duration 15 \\\n     --resolution 720p \\\n     --aspect_ratio 9:16 \\\n     --wait\n   ```\n   Resolution is `480p` or `720p`. Aspect ratio: `auto`\u002F`21:9`\u002F`16:9`\u002F`4:3`\u002F`1:1`\u002F`3:4`\u002F`9:16`. `--generate-audio true` is supported here. Bump `--wait-timeout 30m` for longer ad runs.\n5. **Deliver.** URL + one-line summary (mode, duration).\n\n### Click-to-Ad shortcut (URL-driven)\n\nWhen the user gives a product URL and wants a marketing video in one go:\n\n```bash\n# 1. Trigger fetch (returns the product id and starts background scrape)\nhiggsfield marketing-studio products fetch --url https:\u002F\u002Fshop.example.com\u002Fsneakers --wait\n\n# 2. Generate the marketing video against the same URL — backend reuses the entity\nhiggsfield generate create marketing_studio_video \\\n  --url https:\u002F\u002Fshop.example.com\u002Fsneakers \\\n  --mode ugc \\\n  --duration 15 \\\n  --aspect_ratio 9:16 \\\n  --wait\n```\n\nBackend dedupes by URL, so repeated runs reuse the existing entity instead of re-fetching.\n\n### Workflow — marketing image\n\nSame as above but use `marketing_studio_image` model:\n\n```bash\nhiggsfield generate create marketing_studio_image \\\n  --prompt \"...\" \\\n  --aspect_ratio 1:1 \\\n  --resolution 2k \\\n  --wait\n```\n\n## Errors\n\n- `Missing required params: prompt` → user gave no prompt; ask for it.\n- `Invalid values: aspect_ratio=99:99 (allowed: ...)` → bad enum; pick from allowed.\n- `Unknown params: foo` → schema doesn't accept that flag; check `higgsfield model get \u003Cjst>`.\n- `Session expired` → `higgsfield auth login`.\n\nSee `references\u002Ftroubleshooting.md` for more.\n\n## Anti-Patterns\n\n| Anti-pattern | Why it fails | Instead |\n|---|---|---|\n| Using `higgsfield-generate` for product photoshoots | Bypasses the mode-specific prompt enhancer — output is noticeably lower quality for product brand imagery. | Route to `higgsfield-product-photoshoot` any time a product + specific output format is involved. |\n| Batching all context questions upfront | Users disengage when asked 5 things at once. Model choice and media inputs can often be inferred. | Ask at most one clarifying question before submitting. Pick a sensible default. |\n| Using `--generate-audio` with `seedance_2_0` | The flag isn't accepted by Seedance — it silently breaks. | Use `--audio \u003Cpath>` for Seedance lipsync\u002Fsoundtrack; use `--generate-audio true` only for `marketing_studio_video`. |\n| Printing raw job JSON to chat | Dumps internal IDs and noise. Users want a URL. | Always extract and present only the result URL plus a one-line summary. |\n| Picking the wrong model then iterating blind | Costs money and time. | Read `references\u002Fmodel-catalog.md` first, pick the right model once. |\n\n## Reference docs\n\nLoad on demand:\n\n- `references\u002Fmodel-catalog.md` — picking the right model for the task\n- `references\u002Fprompt-engineering.md` — writing prompts that work\n- `references\u002Fmedia-inputs.md` — image\u002Fvideo reference flows\n- `references\u002Ftroubleshooting.md` — common errors and fixes\n- `references\u002Fmarketing-avatars.md` — preset vs custom avatars\n- `references\u002Fmarketing-products.md` — URL fetch vs manual product create\n- `references\u002Fmarketing-modes.md` — every Marketing Studio mode\n\n## Attribution\n\nPorted from [higgsfield-ai\u002Fskills](https:\u002F\u002Fgithub.com\u002Fhiggsfield-ai\u002Fskills) — MIT License, Copyright (c) 2026 Higgsfield AI. Adapted for mktg's drop-in contract on 2026-05-05.\n\nUpstream version: 0.3.0\nUpstream commit: 1dcfe2687c3a9092232bac55c2b6b9ae3fc717d7\n\nDrift detection: if the upstream skill changes, re-run `mktg-steal https:\u002F\u002Fgithub.com\u002Fhiggsfield-ai\u002Fskills` to evaluate the diff.\n","# \u002Fhiggsfield-generate — AI Image & Video Generation via Higgsfield\n\nSubmit jobs to any Higgsfield model. Wraps the `higgsfield` CLI. Covers generic image\u002Fvideo gen and Marketing Studio (branded ads, avatars, products).\n\n## When to use\n\n- User wants an image or video generated by AI — any model, any style\n- \"animate this photo\", \"make a video from an image\", \"img2vid\"\n- \"create a UGC ad\", \"Marketing Studio video\", \"brand video with avatar\"\n- \"import this product URL and make an ad\"\n- \"generate a cinematic still\", \"make a character illustration\"\n- Anything involving Seedance, Kling, Veo, Soul, Nano Banana, Flux, GPT Image\n\n**Route elsewhere if:**\n- User wants to train a reusable face identity → `higgsfield-soul-id`\n- User wants a mode-enhanced product photoshoot → `higgsfield-product-photoshoot`\n- User just needs a one-off image without Higgsfield → `image-gen` (Gemini, free tier)\n\n## On Activation\n\n1. Read `brand\u002Fvoice-profile.md` and `brand\u002Fcreative-kit.md` if present (`creative-kit.md` is written by `\u002Fvisual-style`). Use brand context to inform model choice and prompt style where relevant. All files are optional — zero-context operation is fine.\n2. Check CLI: `higgsfield account status`. If not on `$PATH`, surface install command (see Optional dependency section). If session expired, prompt auth.\n3. Pick a model from the workflow below. Ask one question at a time if context is missing.\n\n## Optional dependency — Higgsfield account\n\nThis skill requires the `@higgsfield\u002Fcli` binary and a Higgsfield account.\n\n**Without the CLI installed**, return a clear actionable error:\n```\nhiggsfield CLI not found. Install with:\n  curl -fsSL https:\u002F\u002Fraw.githubusercontent.com\u002Fhiggsfield-ai\u002Fcli\u002Fmain\u002Finstall.sh | sh\nThen authenticate:\n  higgsfield auth login\n```\n\n**Without an authed Higgsfield account**, the CLI itself surfaces the auth prompt — no special handling needed in the skill.\n\n**Fallback for image generation only:** if the user just needs a one-off image and doesn't have a Higgsfield account, route them to `image-gen` (Gemini, model `gemini-3.1-flash-image-preview`, free tier). Video generation, Marketing Studio, Soul Characters, and product modes have no fallback — they require Higgsfield.\n\n## Step 0 — Bootstrap\n\nBefore any other command, make sure the CLI is installed and authenticated:\n\n1. If `higgsfield` is not on `$PATH`, install it:\n   ```bash\n   curl -fsSL https:\u002F\u002Fraw.githubusercontent.com\u002Fhiggsfield-ai\u002Fcli\u002Fmain\u002Finstall.sh | sh\n   ```\n2. If `higgsfield account status` fails with `Session expired` \u002F `Not authenticated`, ask the user to run `higgsfield auth login` (interactive, opens a browser) and wait for them to confirm before continuing.\n\nSkip both checks if `higgsfield account status` already prints account info.\n\n## UX Rules\n\n1. Be concise. No raw IDs, no JSON dumps in chat. Print result URL when ready.\n2. No internal jargon. Don't narrate \"calling higgsfield cost\", \"polling job\".\n3. Detect the user's language from the first message and reply in it. Technical args (`--aspect_ratio 16:9`) stay English.\n4. Don't batch-ask. Pick a sane default model and ask one thing at a time only if genuinely missing.\n5. Don't pre-estimate cost. Just submit unless the user asks.\n6. Pass `--wait` to `generate create` so the command blocks until done and prints the result URL itself. Avoid the two-step `create` → `wait` pattern.\n\n## Workflow — generic generation\n\n1. **Pick a model.** Practical defaults from production use:\n\n   **Image:**\n   - Brand product visual (Pinterest pin, lifestyle, hero banner, ad pack, virtual try-on) → use `higgsfield-product-photoshoot` instead. NOT this skill.\n   - Branded ad image with avatar + product (Marketing Studio shape) → Marketing Studio Image (see Marketing Studio below)\n   - Aesthetic UGC \u002F fashion editorial \u002F lifestyle character → Soul 2.0\n   - Cinematic still frame → Soul Cinema\n   - Highly characterful creative persona (text-only, distinctive) → Soul Cast\n   - Locations \u002F environments \u002F no-people scenes → Soul Location (best in class)\n   - Vector illustrations OR face edit + complex scene swap → Seedream 4.5\n   - Soul Character (reference id from `higgsfield-soul-id`) → Soul 2.0 for stills, Soul Cinema for cinematic\n   - Fast and cheap iteration → Z Image\n   - Character or cartoon-style work → Nano Banana 2; step up to Nano Banana Pro on hard cases\n   - **Default for everything else → GPT Image 2.** Graphic design, UI, banners, typography, and high-fidelity general generation.\n\n   **Video:**\n   - All advertising \u002F commercial \u002F branded ad video → Marketing Studio (see Marketing Studio below)\n   - **Default all-purpose serious video (multi-shot, consistent identity, motion-heavy) → Seedance 2.0.** SOTA.\n   - Single-plane scene without strong dynamics, cheaper than Seedance 2.0 → Kling 3.0\n   - Cheap clean shot without cuts → Seedance 1.5 Pro\n   - Cinema-grade highest fidelity → Cinema Studio Video 3.0\n   - Cheap with strong physics, no audio needed → Minimax Hailuo\n   - Fast batch \u002F volume → Veo 3.1 Lite\n\n   For the actual `--model` ID to pass to `higgsfield generate create`, run `higgsfield model list --json | jq` to map display names to IDs. See `references\u002Fmodel-catalog.md` for the full table.\n\n2. **Pass media inputs straight to flags.** Media flags accept a local file path **or** a UUID. CLI auto-uploads paths and auto-detects job vs upload for UUIDs. No need to pre-upload. Each model declares accepted roles (`image`, `start_image`, `end_image`, `video`, `audio`) — see `references\u002Fmedia-inputs.md`.\n3. **Validate quickly.** If unsure of params, run `higgsfield model get \u003Cjst> --json` once and pass only what's needed. Use schema defaults otherwise. The server returns `adjustments` for non-fatal coercions and a structured error for invalid declared-param values.\n4. **Submit and wait in one shot.** `higgsfield generate create \u003Cjst> --prompt \"...\" [media flags] [param flags] --wait`. Blocks until terminal status and prints the result URL on stdout. Tunables: `--wait-timeout 20m` (default 10m), `--wait-interval 5s` (default 3s).\n5. **Deliver.** Send the URL plus a one-line summary (model, duration if video).\n\nTo inspect or rerun later, `higgsfield generate list --json` and `higgsfield generate get \u003Cid> --json` work for retrospection. `higgsfield generate wait \u003Cid>` is still available if you ever need to rejoin a job started without `--wait`.\n\n## Media flags\n\n| Flag | Use for | Models that accept it |\n|---|---|---|\n| `--image \u003Cpath-or-id>` | reference image | most image models, `seedance_2_0`, `veo3`, `marketing_studio_video` |\n| `--start-image \u003Cpath-or-id>` | first frame for image-to-video transitions | `kling3_0`, `kling2_6`, `veo3_1`, `seedance_2_0`, `marketing_studio_video` |\n| `--end-image \u003Cpath-or-id>` | last frame for transitions | `kling3_0`, `seedance_2_0`, `marketing_studio_video` |\n| `--video \u003Cpath-or-id>` | reference video | `seedance_2_0` |\n| `--audio \u003Cpath-or-id>` | reference audio (lipsync, soundtrack match) | `seedance_2_0` (use this, NOT `--generate-audio`) |\n\nEach flag accepts either a local file path (auto-uploaded) or a UUID. See `references\u002Fmedia-inputs.md` for the full table.\n\n## Common params\n\nFlags pass through to model schema. Use `higgsfield model get \u003Cjst>` to discover.\n\n```bash\nhiggsfield generate create gpt_image_2 --prompt \"neon city at dusk\" --aspect_ratio 16:9 --resolution 2k --wait\nhiggsfield generate create nano_banana_2 --prompt \"anime character concept, expressive pose\" --image .\u002Fref.png --wait\nhiggsfield generate create seedance_2_0 --prompt \"camera dollies in\" --start-image .\u002Ffirst.png --duration 8 --wait\nhiggsfield generate create text2image_soul_v2 --prompt \"...\" --soul-id \u003Csoul_ref_id> --wait\n```\n\nFor machine-readable output, add `--json`. With `--wait --json` you get the final job object array.\n\nStdin prompt: `echo \"...\" | higgsfield generate create z_image --wait`.\n\n## Marketing Studio\n\nBranded image\u002Fvideo gen: avatars + products + ad-style modes. Use models `marketing_studio_video` and `marketing_studio_image`.\n\n### Concepts\n\n- **Avatar** — presenter face. Curated `preset` (browse `higgsfield marketing-studio avatars list`) or `custom` (uploaded photos via `higgsfield marketing-studio avatars create`).\n- **Product** — brand item with title + reference images. Imported from URL (`higgsfield marketing-studio products fetch --url ...`) or created from uploaded images (`higgsfield marketing-studio products create`).\n- **Webproduct** — App Store \u002F web page version. Auto-routes when fetching App Store URLs.\n\n### UX rules (additional)\n\n- One question per phase. Don't ask product+avatar+mode upfront.\n\n### Workflow — quick ad video\n\n1. **Get product.**\n   - URL → `higgsfield marketing-studio products fetch --url \u003Curl> --wait` (polls until import done)\n   - Local images → `higgsfield upload create \u003Cphoto>...` then `higgsfield marketing-studio products create --title \"...\" --image \u003Cid>...`\n   Capture product id.\n2. **Pick avatar.**\n   - Default: `higgsfield marketing-studio avatars list` and pick a preset matching the brand voice.\n   - Custom: `higgsfield marketing-studio avatars create --name \"...\" --image \u003Cupload_id>`.\n3. **Pick mode.** Default `ugc`. Other slugs: `tutorial`, `ugc_unboxing`, `hyper_motion`, `product_review`, `tv_spot`, `wild_card`, `ugc_virtual_try_on`, `virtual_try_on`. See `references\u002Fmarketing-modes.md`.\n4. **Generate (one-shot).**\n   ```bash\n   higgsfield generate create marketing_studio_video \\\n     --prompt \"...\" \\\n     --avatars '[{\"id\":\"\u003Cavatar_id>\",\"type\":\"preset\"}]' \\\n     --product_ids '[\u003Cproduct_id>]' \\\n     --mode ugc \\\n     --duration 15 \\\n     --resolution 720p \\\n     --aspect_ratio 9:16 \\\n     --wait\n   ```\n   Resolution is `480p` or `720p`. Aspect ratio: `auto`\u002F`21:9`\u002F`16:9`\u002F`4:3`\u002F`1:1`\u002F`3:4`\u002F`9:16`. `--generate-audio true` is supported here. Bump `--wait-timeout 30m` for longer ad runs.\n5. **Deliver.** URL + one-line summary (mode, duration).\n\n### Click-to-Ad shortcut (URL-driven)\n\nWhen the user gives a product URL and wants a marketing video in one go:\n\n```bash\n# 1. Trigger fetch (returns the product id and starts background scrape)\nhiggsfield marketing-studio products fetch --url https:\u002F\u002Fshop.example.com\u002Fsneakers --wait\n\n# 2. Generate the marketing video against the same URL — backend reuses the entity\nhiggsfield generate create marketing_studio_video \\\n  --url https:\u002F\u002Fshop.example.com\u002Fsneakers \\\n  --mode ugc \\\n  --duration 15 \\\n  --aspect_ratio 9:16 \\\n  --wait\n```\n\nBackend dedupes by URL, so repeated runs reuse the existing entity instead of re-fetching.\n\n### Workflow — marketing image\n\nSame as above but use `marketing_studio_image` model:\n\n```bash\nhiggsfield generate create marketing_studio_image \\\n  --prompt \"...\" \\\n  --aspect_ratio 1:1 \\\n  --resolution 2k \\\n  --wait\n```\n\n## Errors\n\n- `Missing required params: prompt` → user gave no prompt; ask for it.\n- `Invalid values: aspect_ratio=99:99 (allowed: ...)` → bad enum; pick from allowed.\n- `Unknown params: foo` → schema doesn't accept that flag; check `higgsfield model get \u003Cjst>`.\n- `Session expired` → `higgsfield auth login`.\n\nSee `references\u002Ftroubleshooting.md` for more.\n\n## Anti-Patterns\n\n| Anti-pattern | Why it fails | Instead |\n|---|---|---|\n| Using `higgsfield-generate` for product photoshoots | Bypasses the mode-specific prompt enhancer — output is noticeably lower quality for product brand imagery. | Route to `higgsfield-product-photoshoot` any time a product + specific output format is involved. |\n| Batching all context questions upfront | Users disengage when asked 5 things at once. Model choice and media inputs can often be inferred. | Ask at most one clarifying question before submitting. Pick a sensible default. |\n| Using `--generate-audio` with `seedance_2_0` | The flag isn't accepted by Seedance — it silently breaks. | Use `--audio \u003Cpath>` for Seedance lipsync\u002Fsoundtrack; use `--generate-audio true` only for `marketing_studio_video`. |\n| Printing raw job JSON to chat | Dumps internal IDs and noise. Users want a URL. | Always extract and present only the result URL plus a one-line summary. |\n| Picking the wrong model then iterating blind | Costs money and time. | Read `references\u002Fmodel-catalog.md` first, pick the right model once. |\n\n## Reference docs\n\nLoad on demand:\n\n- `references\u002Fmodel-catalog.md` — picking the right model for the task\n- `references\u002Fprompt-engineering.md` — writing prompts that work\n- `references\u002Fmedia-inputs.md` — image\u002Fvideo reference flows\n- `references\u002Ftroubleshooting.md` — common errors and fixes\n- `references\u002Fmarketing-avatars.md` — preset vs custom avatars\n- `references\u002Fmarketing-products.md` — URL fetch vs manual product create\n- `references\u002Fmarketing-modes.md` — every Marketing Studio mode\n\n## Attribution\n\nPorted from [higgsfield-ai\u002Fskills](https:\u002F\u002Fgithub.com\u002Fhiggsfield-ai\u002Fskills) — MIT License, Copyright (c) 2026 Higgsfield AI. Adapted for mktg's drop-in contract on 2026-05-05.\n\nUpstream version: 0.3.0\nUpstream commit: 1dcfe2687c3a9092232bac55c2b6b9ae3fc717d7\n\nDrift detection: if the upstream skill changes, re-run `mktg-steal https:\u002F\u002Fgithub.com\u002Fhiggsfield-ai\u002Fskills` to evaluate the diff.\n",{"name":5,"reads":63,"author":66,"writes":67,"license":15,"version":68,"metadata":69,"description":72,"allowed-tools":73,"argument-hint":78,"user-invocable":79},[64,65],"brand\u002Fvoice-profile.md","brand\u002Fcreative-kit.md","Higgsfield AI (ported by moiz)",[],"0.3.0",{"openclaw":70},{"emoji":71},"?","Use when the user wants to generate an image or video via Higgsfield AI. Covers\n30+ models: Soul V2, Seedance 2.0, Kling 3.0, Veo 3.1, GPT Image 2, Nano Banana 2.\nAlso covers Marketing Studio — branded ad video\u002Fimage with avatars and products.\nUse whenever: \"generate an image\", \"make a video\", \"animate this photo\",\n\"image-to-video\", \"img2vid\", \"edit this image with AI\", \"produce a clip\",\n\"create an ad\", \"make a UGC video\", \"marketing video\", \"brand video\",\n\"TV spot\", \"import product from URL\", \"create avatar for ad\",\n\"Seedance\", \"Kling\", \"Veo\", \"Soul gen\", \"Nano Banana\", \"Marketing Studio\".\nChain with higgsfield-soul-id when user wants a reusable face identity.\nOwns AI-generated \"marketing video\" \u002F \"brand video\" \u002F ad creative.\nNOT for: training a Soul Character (use higgsfield-soul-id), product photoshoots\nwith mode-specific enhancer (use higgsfield-product-photoshoot), text\u002FTTS,\nscreen-recorded product demos (use marketing-demo), slides-to-MP4 assembly\n(use video-content), Remotion code (use remotion-best-practices).\nRequires Higgsfield CLI installed and authed.\n",[50,74,75,76,77],"Read","Write","Edit","Skill","[prompt] [--model \u003Cname>] [--image \u003Cpath-or-id>]",true,"main","65a0c0d1e5a6f4ac9fb5281a72c91cbf7e9257aa","skills\u002Fhiggsfield-generate",5,"https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli","https:\u002F\u002Fwww.marketing-cli.com\u002F","https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf","https:\u002F\u002Fmoiz.ai","AI Engineer\r\n","2026-10-20 15:05:36",{"source":8,"skillName":5,"commands":91,"prompt":101,"zipAvailable":79},[92,95,98],{"tool":93,"command":94},"npx","npx skills add MoizIbnYousaf\u002Fmarketing-cli --skill higgsfield-generate",{"tool":96,"command":97},"bunx","bunx skills add MoizIbnYousaf\u002Fmarketing-cli --skill higgsfield-generate",{"tool":99,"command":100},"pnpm","pnpm dlx skills add MoizIbnYousaf\u002Fmarketing-cli --skill higgsfield-generate","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fhiggsfield-generate\u002FSKILL.md",[103,109,113,117,121,125,129,133],{"path":104,"resourceType":105,"resourceTypeDesc":106,"sizeBytes":107,"sourceHtmlUrl":108},"index.json","REFERENCE","参考文档",678,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fcompliance\u002Fiso\u002Fframework\u002Faudit\u002Findex.json",{"path":110,"resourceType":105,"resourceTypeDesc":106,"sizeBytes":111,"sourceHtmlUrl":112},"references\u002Fmarketing-avatars.md",1080,"https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fhiggsfield-generate\u002Freferences\u002Fmarketing-avatars.md",{"path":114,"resourceType":105,"resourceTypeDesc":106,"sizeBytes":115,"sourceHtmlUrl":116},"references\u002Fmarketing-modes.md",2954,"https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fhiggsfield-generate\u002Freferences\u002Fmarketing-modes.md",{"path":118,"resourceType":105,"resourceTypeDesc":106,"sizeBytes":119,"sourceHtmlUrl":120},"references\u002Fmarketing-products.md",1456,"https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fhiggsfield-generate\u002Freferences\u002Fmarketing-products.md",{"path":122,"resourceType":105,"resourceTypeDesc":106,"sizeBytes":123,"sourceHtmlUrl":124},"references\u002Fmedia-inputs.md",3901,"https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fhiggsfield-generate\u002Freferences\u002Fmedia-inputs.md",{"path":126,"resourceType":105,"resourceTypeDesc":106,"sizeBytes":127,"sourceHtmlUrl":128},"references\u002Fmodel-catalog.md",11529,"https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fhiggsfield-generate\u002Freferences\u002Fmodel-catalog.md",{"path":130,"resourceType":105,"resourceTypeDesc":106,"sizeBytes":131,"sourceHtmlUrl":132},"references\u002Fprompt-engineering.md",1554,"https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fhiggsfield-generate\u002Freferences\u002Fprompt-engineering.md",{"path":134,"resourceType":105,"resourceTypeDesc":106,"sizeBytes":135,"sourceHtmlUrl":136},"references\u002Ftroubleshooting.md",1196,"https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fhiggsfield-generate\u002Freferences\u002Ftroubleshooting.md",[138,158,184,214,238,263],{"skillNo":139,"name":140,"nameZh":6,"description":141,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":142,"categories":143,"keywords":144,"publishedAt":58},"01M6DKQDNVS30J8TB3YYM13PJ2","cmo-studio-integration","When mktg-studio is running on this machine, \u002Fcmo proactively narrates work into the dashboard via Bash + curl against the localhost HTTP API. Detect via \u002Fapi\u002Fhealth, then log every meaningful action — the user sees what \u002Fcmo is doing in real time.","https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fstudio\u002Fskills\u002Fcmo-studio-integration\u002FSKILL.md",[],[145,146,147,148,149,150,151,152,50,153,154,155,156,157],"integration","cmo","cmo studio integration","real time","dashboard","http","api","health","work","curl","user","log","time",{"skillNo":159,"name":160,"nameZh":6,"description":161,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":162,"categories":163,"keywords":168,"publishedAt":58},"01M6DKQ8KH8EZ27YY7PEDSZGMT","voice-extraction","Reverse-engineer any person's writing voice from their content. Paste in posts, articles, tweets, or essays and this skill launches 10 parallel Sonnet subagents to analyze every dimension of the voice, then synthesizes into a voice file. Use when someone says 'match this voice,' 'analyze this writing,' 'extract their voice,' 'make me sound like this,' 'study this person's writing,' or pastes in content they want to learn from.","https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fvoice-extraction\u002FSKILL.md",[164,165],{"categoryNo":27,"categoryName":28,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":166,"categoryName":167,"taxonomyType":32,"taxonomyTypeDesc":33},"01JBSEEDCAT000000000000036","内容创作者",[169,170,171,172,173,174,175,176,177,178,179,180,181,182,183],"extraction","voice","voice extraction","writing","learn","content","file","analyze","parallel","extract","subagents","use","engineer","study","me",{"skillNo":185,"name":186,"nameZh":6,"description":187,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":188,"categories":189,"keywords":195,"publishedAt":58},"01M6DKPZAQ4NTERXENEFKFACZZ","visual-style","Build a persistent visual brand identity for image generation. Defines how the brand looks visually — aesthetic, lighting, composition, mood — and writes it to brand\u002Fcreative-kit.md so \u002Fimage-gen and other creative skills produce consistent on-brand visuals. Three modes: Extract (from website\u002FURL), Build (interview), Reference (mood board\u002Fexamples). Use when starting any project that needs images, when the user says \"visual style\", \"brand aesthetic\", \"image style\", \"visual identity\", \"how should our images look\", \"build visual brand\", \"define our look\", or when \u002Fimage-gen outputs feel generic because no visual style exists yet.","https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fvisual-style\u002FSKILL.md",[190,193,194],{"categoryNo":191,"categoryName":192,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":30,"categoryName":31,"taxonomyType":32,"taxonomyTypeDesc":33},[196,197,198,49,199,200,201,202,203,204,205,206,180,207,208,209,210,211,212,213],"visual","style","visual style","identity","visuals","produce","website","Composition","how","brand","interview","images","aesthetic","three","lighting","positioning","project","define",{"skillNo":215,"name":216,"nameZh":6,"description":217,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":218,"categories":219,"keywords":225,"publishedAt":58},"01M6DKPR2K3YJ1MAJG8XT815VP","video-content","Three-tier video pipeline: ffmpeg Quick (5s, instant) → ffmpeg Enhanced with Ken Burns (15s, polished) → Remotion Animated (60-90s, production-grade). Takes static slides from Paper MCP or any PNGs and assembles them into platform-ready video. Make sure to use this skill whenever the user has slides, images, or PNGs and wants to turn them into video — even if they just say 'make a video from these', 'animate my slides', 'I have images and need a TikTok', or 'stitch these together'. Also use when they mention ffmpeg video assembly, Remotion-animated slide assembly, Ken Burns effects, or any slides-to-video pipeline. Owns the slides→MP4 assembly pipeline; for writing, debugging, or running `remotion render` on Remotion code itself, see \u002Fremotion-best-practices; for screen-recorded product demos, see \u002Fmarketing-demo. Works with any PNG source — Paper exports, Canva, screenshots, anything.","https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Fvideo-content\u002FSKILL.md",[220,221,222,223,224],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":27,"categoryName":28,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":35,"categoryName":36,"taxonomyType":32,"taxonomyTypeDesc":33},{"categoryNo":166,"categoryName":167,"taxonomyType":32,"taxonomyTypeDesc":33},[174,52,226,227,172,228,229,54,53,230,51,50,231,232,233,234,207,235,236,237],"video content","MCP","status","debugging","pipeline","marketing","instant","assemble","ready","stitch","tiktok","screen",{"skillNo":239,"name":240,"nameZh":6,"description":241,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":242,"categories":243,"keywords":249,"publishedAt":58},"01M6DKPKDPTV6JFSW4SK3CKQCH","typefully","Create, schedule, and manage social media posts via Typefully. ALWAYS use this skill when asked to draft, schedule, post, or check tweets, posts, threads, or social media content for Twitter\u002FX, LinkedIn, Threads, Bluesky, or Mastodon.","https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Ftypefully\u002FSKILL.md",[244,245,246,247,248],{"categoryNo":191,"categoryName":192,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":27,"categoryName":28,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":30,"categoryName":31,"taxonomyType":32,"taxonomyTypeDesc":33},{"categoryNo":35,"categoryName":36,"taxonomyType":32,"taxonomyTypeDesc":33},[240,55,250,251,50,231,170,205,252,253,254,255,256,180,257,258,259,260,261,262],"SET","Media","schedule","twitter","linkedin","social media","check","manage","bluesky","social","draft","distribution","scripts",{"skillNo":264,"name":265,"nameZh":6,"description":266,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":267,"categories":268,"keywords":273,"publishedAt":58},"01M6DKP7X0YHAK9QZ1ZRKFQ596","tiktok-slideshow","Orchestrator skill that chains \u002Fslideshow-script → \u002Fpaper-marketing → \u002Fvideo-content for end-to-end TikTok slideshow production. Each phase is an independent Lego block — this orchestrator is just one recipe that combines them. Produces 5 publishable TikTok videos from a single positioning angle. Triggers on \"TikTok slideshow\", \"TikTok video\", \"make TikTok\", \"slideshow video\", \"TikTok content\".","https:\u002F\u002Fgithub.com\u002FMoizIbnYousaf\u002Fmarketing-cli\u002Fblob\u002Fmain\u002Fskills\u002Ftiktok-slideshow\u002FSKILL.md",[269,270,271,272],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":27,"categoryName":28,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":35,"categoryName":36,"taxonomyType":32,"taxonomyTypeDesc":33},[236,274,228,174,275,52,51,50,231,276,277,278,211,279,280,281,282],"tiktok slideshow","Production","just","orchestrator","bun","end","triggers","ffmpeg","paper"]